Surveillance of alcohol use through population surveys in the Americas from 2010 to 2019
Bibliographic record
Abstract
AIMS: The aims of this study were to identify alcohol-related population surveys administered in the Americas, determine which alcohol-related measures are examined and identify coverage gaps regarding alcohol-related measures. METHODS: As part of the Global Information System on Alcohol and Health study, a systematic search was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria to identify regionally or nationally representative survey reports of the general population from 1 January 2010 to 6 August 2019. Alcohol-related measures extracted from surveys were categorized into 10 domains: alcohol consumption status; alcohol consumption; unrecorded alcohol consumption; drinking patterns; symptoms of dependence and/or harmful use; drinking during pregnancy; treatment coverage; second-hand harms; economic; and other. RESULTS: The systematic search identified 7417 survey reports, 94 of which were new and included in this study, with an additional 11 studies included from a previous systematic study of alcohol surveys. In total, 94 unique surveys and 161 unique survey waves were located, representing 105 unique survey questionnaires covering 30 countries. No population surveys were found for five member states; namely, Antigua and Barbuda, Dominica, Haiti, Saint Vincent and the Grenadines and Saint Kitts and Nevis. All countries with population-based alcohol surveys had had a population survey probing alcohol use in the past year/month. Questions regarding heavy episodic drinking, alcohol use disorders, treatment-seeking for alcohol use, drinking during pregnancy, harms to others and the amounts spent on alcohol were asked in 26, 25, 10, 6, 22 and 11 countries, respectively. CONCLUSIONS: The heterogeneity in alcohol-related population surveys in the Americas from 2010 to 2019 limits their comparability throughout countries and over time. Future surveys should implement a standardized set of core questions to provide consistency in the monitoring of alcohol consumption and alcohol-related harms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".